• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5C
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• pp.171-185
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• 2011

Ready-mixed shotcrete that mixed with high quality aggregate and can improve construction quality is produced in a dry mortar plant and transported to construction sites. Because of using aggregate that produced in a special plant, Ready-mixed shotcrete has many advantages : good grain-size distribution, minimum stone powder, high quality and standardization material, etc. In this basic study different from the existing study that limited to additive and accelerator, the improvement of aggregate quality was tried to upgrade the shotcrete performance. The investigation about the construction conditions of shotcrete was performed and the result of an opinion poll was analyzed for a good grasp of the problems in domestic shotcrete quality. Pilot Plant Test was also performed to minimize the material segregation in plant manufacturing process. In additions, the field test was performed to find the optimum contents of synthetic fiber, appearing the same flexible toughness with that of steel fiber, and to find the optimum replacement ratio of blast furnace slag.

• Journal of the Korea Concrete Institute
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• v.17 no.3 s.87
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• pp.329-334
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• 2005

The use of Polymer Concrete (PC) is growing very rapidly in many structural and construction applications such as box culverts, hazardous waste containers, trench lines, floor drains and the repair and overlay of damaged cement concrete surfaces in pavements, bridges, etc. However, PC has a defect economically because resin which be used for binder is expensive. Therefore the latest research is being progressed to replace existing resin with new resin which can reduce the high cost. Here, Polymer concrete using the recycled PET(polyethylene terephthalate) has some merits such as decrease of environmental destruction, decrease of environmental pollution and development of new construction materials. The variables of this study are amount of resin, curing condition and maximum size of coarse aggregate to find out mechanic properties of this. Stress-strain curve was obtained using MTS equipment by strain control. The results indicated that modulus of elasticity was increased gradually in an ascending branch of curve, as an increase of resin content. Compressive strength was the highest for resin content of $13\%$. And Compressive strength was increased as maximum size of coarse aggregate increases. The strain at maximum stress increases with an increase of resin content and size of coarse aggregate. For the descending branch of stress-strain curve the brittle fracture was decreased when it was cured at the room temperature compared to high temperature.

• International Journal of Highway Engineering
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• v.11 no.2
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• pp.1-15
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• 2009

Surface of exposed aggregate concrete pavements is consists of exposed coarse aggregate by removing upper 2$\sim$3mm mortar of concrete slab. Exposed aggregate concrete pavements have advantages of maintaining low-noise and adequate skid-resistance level during the performance period. In order to provide the successful exposed concrete aggregate pavement, uniform distribution of the coarse aggregate on pavement surface through adequate the mix design and exposing method. The mix design in concrete pavement is generally designed on the basis of strength, but mix design of exposed aggregate pavement employed in this study includes the consideration of noise and skid resistance, as well as strength. Smaller of maximum coarse aggregate is known to be effective for reduce noise level. Optimum mix design and exposing method of fine-size exposed aggregate portland cement concrete pavement that can reducing the noise and maintain the adequate level of skid resistance are proposed in this study. To consider the variation of optimum exposing time due to the hardening speed of mortar by climatic condition, quantitative is also suggested measurement of hardening state.

• Computers and Concrete
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• v.10 no.2
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• pp.197-217
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• 2012

This research deals with the prediction of compressive strength of normal and high strength concrete using neural networks. The compressive strength was modeled as a function of eight variables: quantities of cement, fine aggregate, coarse aggregate, micro-silica, water and super-plasticizer, maximum size of coarse aggregate, fineness modulus of fine aggregate. Two networks, one using raw variables and another using grouped dimensionless variables were constructed, trained and tested using available experimental data, covering a large range of concrete compressive strengths. The neural network models were compared with regression models. The neural networks based model gave high prediction accuracy and the results demonstrated that the use of neural networks in assessing compressive strength of concrete is both practical and beneficial. The performance of model using the grouped dimensionless variables is better than the prediction using raw variables.

• Journal of the Korea Concrete Institute
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• v.25 no.5
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• pp.477-484
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• 2013

In this study, eleven reinforced concrete beams, ground granulated blast furnace slag, replacing recycled coarse aggregate (BRS series) and recycled coarse aggregate with steel fiber (BSRS series), and standard specimen (BSS) were constructed and tested under monotonic loading. Experimental programs were carried out to improve and evaluate the shear performance of such test specimens, such as the load-displacement, the failure mode and the maximum load carrying capacity. All the specimens were modeled in 1/2 scale-down size. Test results showed that test specimens (BSRS Series) was increased the compressive strength by 9%, the maximum load carrying capacity by 1~6% and the ductility capacity by 1.02~1.13 times in comparison with the standard specimen (BSS). And the specimens (BSRS Series) showed enough ductile behavior and stable flexural failure.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.6
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• pp.1-10
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• 2014

In this study, thirteen reinforced concrete beams, ground granulated blast furnace slag, replacing recycled coarse aggregate with PVA fiber (BSPG series) and recycled coarse aggregate with hybrid fiber ($BSPGR_1$, $BSPGR_2$ series), and standard specimen (BSS) were constructed and tested under monotonic loading. Experimental programs were carried out to improve and evaluate the Structural performance of such test specimens, such as the load-displacement, the failure mode, and the maximum load carrying capacity. All the specimens were modeled in 1/2 scale-down size. Test results showed that test specimens ($BSPGR_1$, $BSPGR_2$ series) was increased the compressive strength by 13%, the maximum load carrying capacity by 4~21% and the ductility capacity by 4~28% in comparison with the standard specimen (BSS). And the specimens ($BSPGR_1$, $BSPGR_2$ series) showed enough ductile behavior and stable flexural failure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.342-347
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• 2016

This study examined the effects of the coarse aggregate maximum size and grading of fine aggregates to acquire the characteristics of very low shrinkage on normal strength concrete mixed in the field. In addition, the shrinkage characteristics of concrete under construction were evaluated in accordance with the curing temperature. The compressive strength and drying shrinkage tests were performed for nine mixing factors composed of the coarse aggregate size (13, 20, and 25 mm), types of fine aggregate (see sand, crushed sand, and blended sand), and curing temperatures (5, 20, and $35^{\circ}C$). To acquire low shrinkage properties under $350{\mu}{\varepsilon}$ strain on normal strength concrete, a 25 mm maximum of coarse aggregate was available, and the grading of fine aggregate affected the shrinkage of concrete. In addition, very low shrinkage properties were acquired in the curing temperature range except cold and hot weather concrete.

• Journal of the Korean Geotechnical Society
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• v.32 no.12
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• pp.23-32
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• 2016

A single particle crushing test was carried out for recycled aggregates from waste concrete while demolishing various structures. When the recycled aggregates were used for backfill or road subbase materials, load-displacement and crushing characteristics were analyzed. The recycled aggregates with hydrates and aggregates were sorted into 40 mm size (75-40 mm) and 20 mm size (40-20 mm). At initial loading, their irregular surface was closed to and then crushed by loading plate. Such first crushing stage was called 'Surface crushing'. Further loading, some hydrate was crushed and detached from aggregate, and such process repeated several times. This state is called 'hydrate crushing'. The final state is called 'aggregate crushing' in which aggregate crushed and following load suddenly dropped down. As the load increased, such crushing cycle is repeated several times. The shapes of aggregates are round or square, and triangle or long shaped. Depending on their shapes and surface conditions, they crushed in different ways. The 63% of aggregates showed more than 50% load reduction due to aggregate crushing. The 90% load reduction occurred at 15% of aggregates. The 40 mm aggregate crushed at maximum load between 3.05-4.38 kN and 70% of crushed aggregates were less than 20 mm.

• Computers and Concrete
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• v.22 no.4
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• pp.355-363
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• 2018

In the following paper, a socio-political heuristic search approach, named the imperialist competitive algorithm (ICA) has been used to improve the efficiency of the multi-layer perceptron artificial neural network (ANN) for predicting the compressive strength of concrete. 173 concrete samples have been investigated. For this purpose the values of slump flow, the weight of aggregate and cement, the maximum size of aggregate and the water-cement ratio have been used as the inputs. The compressive strength of concrete has been used as the output in the hybrid ICA-ANN model. Results have been compared with the multiple-linear regression model (MLR), the genetic algorithm (GA) and particle swarm optimization (PSO). The results indicate the superiority and high accuracy of the hybrid ICA-ANN model in predicting the compressive strength of concrete when compared to the other methods.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1294-1301
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• 2010

This study is an experimental research for the dispersion behavior and impact characteristics of debris flow according to change of slope. Large scale experimental setup for the debris flow was established to simulate the artificial rainfall and control the ground slope. Parameters such as materials of debris flow, slope, and length of slope were used for the experiments. After the experiments, it was found that the speed of ground material components was increased about 28~47%. It was found that speed can be increased by increasing the particle size. Furthermore, maximum/final loads for ground material components were increased 89% for the coarse aggregate and 68% for the fine aggregate comparing with sand.